System for Measuring and Reporting Weight-Training Performance Metrics

ABSTRACT

A system for measuring weight-lifting performance is described. The system comprises a collar that may be attached to a weight bar, wherein the collar comprises at least one motion sensor, at least one touch sensor, and a signal processor. The motion sensors comprise a barometric altimeter, a gyroscope, and/or an accelerometer that measure the motion of the weight bar during a lifting activity. Signals from the motion sensors are interpreted by the signal processor as physical activity data, which are then wirelessly transmitted to a multimedia device having a data processor. The data processor is configured to calculate performance metrics from the physical activity data and to display them to a user via a display on the multimedia device. Athletes may use the performance metric outputs from the data processor to monitor the form of their lifting exercises for training purposes, safety considerations, and self-improvement.

BACKGROUND OF THE INVENTION

This disclosure relates generally to fitness equipment and in particularto a system for measuring and reporting performance metrics duringweightlifting exercises.

Weightlifting is a popular form of recreational and competitiveexercise. In an effort to improve their performance, athletes andpersons may track their strength training progress by recordingrepetitions and mass lifted. To prevent against injury and to optimizethe incremental benefits of training, athletes and persons may monitortheir form to ensure proper technique. Because it can be difficult forathletes or persons to assess their own lifting form without an externalreference, a means of providing immediate feedback during a workoutwould improve the efficacy of training regimens. Competitive fitnessactivities are adjudicated via a combination of repetitions, weightlifted, and form achieved, and so it may be beneficial to an athlete totrack these parameters via real time metrics. Having access to saidphysical activity data can allow a person to measure their performance,reduce injury risk, and make informed decisions about their exerciseregimen. Sensors may be used to detect, measure, and transmit physicalactivity data, and processors within multimedia devices or othercomputing means may be used to receive and interpret said data and tocalculate and display performance metrics calculated therefrom.

SUMMARY OF THE INVENTION

Accordingly, the present invention provides a system for measuring andreporting performance metrics during weightlifting exercises. The systemmay comprise a collar configured to attach to a weight bar, wherein thecollar comprises at least one touch sensor, at least one motion sensor,and a signal processor, wherein the signal processor is configured toreceive signals from said touch and motion sensors, determine physicalactivity data using said signals, and deliver said physical activitydata to a multimedia device. The multimedia device (hereafter referredto as “the device”) may comprise a mobile or stationary electronicdevice, such as a smart phone or tablet computer. The device may beremote from the collar and may further comprise a data processor,wherein the data processor may be configured to receive said physicalactivity data from the signal processor and calculate performancemetrics that characterize an activity performed by a user, such as anathlete or person performing weightlifting exercises. The device may befurther configured to store, transmit, or display said performancemetrics to said user.

During an exercise regimen, a user may attach the collar to either endof a cylindrical weight bar. The collar may attach via at least oneclamp and an articulated hinge, or it may slide onto the bar. The touchsensors may be configured to sense if the collar is attached to theweight bar. The motion sensors may be configured to sense physicalmotion of the weight bar and to take measurements of the characteristicsof said motion. Once the touch sensors indicate that the collar isattached to the weight bar, the signal processor may be configured toreceive and record signals from the motion sensors and determinephysical activity data therefrom. The sensors and the signal processormay be enclosed by a case attached to the clamp. Alternatively some orall of the sensors may be attached to an external face of said case.

The motion sensors may comprise an accelerometer, a gyroscope, and/or apressure sensor such as a barometric altimeter. The motion sensors mayrelay signals to the signal processor and the signal processor may beconfigured to convert the signals into physical activity data. Forexample, as the user lifts the weight bar with the collar attached toeither end, the signal processor may be configured to interpret signalsfrom the accelerometer to measure the acceleration at which the weightbar is lifted, to interpret the signals from the gyroscope to measurethe orientation of the weight bar relative to an axis, and to interpretthe signals from the barometric altimeter to measure the height of theweight bar from the ground. The signal processor may further beconfigured to transmit the physical data over a communications networkto the multimedia device. The communications network may comprise awireless connection between the signal processor and the multimediadevice.

The multimedia device may comprise a data processor configured toreceive physical activity data from the signal processor and tocalculate weightlifting performance metrics from the physical activitydata. Performance metrics may comprise parameters that characterize theaction taken by the user during an activity involving the weight bar,such as a lift. The data processor may be capable of executing softwareinstructions and may employ a software application or App having aninterface configured to accept inputs from a user. The softwareapplication or App may be configured to display said performance metricsvia a visual or graphical representation on the multimedia device.Performance metrics may be calculated based on input from a user or maybe automatically or programmatically determined. Those performancemetrics which are determined and displayed may correspond to particularactivities undertaken with the weight bar by a user.

The data processor in the multimedia device may also be configured toanalyze the performance metrics it has calculated and to output anassessment of the form of a lift of the weight bar with the collarattached thereto, also referred to as the “lift form”. Lift form is animportant determination for an athlete undertaking weightliftingactivities, as proper lifting technique can prevent injury and improveathletic performance. Lift form shall be understood as a quantitative orqualitative assessment of proper lifting technique that takes intoconsideration a plurality of performance metrics related to a particularactivity undertaken by the user lifting the weight bar. Performancemetrics may comprise the velocity at which the weight bar is lifted, theorientation of the weight bar, the height of the weight bar during alift, the movement path of the weight bar, the number of repetitions ofsaid lift, the duration of lifts and holds of the weight bar, and forcesexerted by the user on the weight bar, among others. The data processormay analyze performance metrics and output a grade, score, suggestion,evaluation, and/or other means of assessment to provide feedback to theuser.

In certain embodiments, the system of the present invention may furthercomprise at least two cameras configured to view a user and the weightbar during weightlifting exercises and at least one light mounted to anend of the weight bar. The light may comprise a light emitting diode oranother device emitting suitably discernible illumination or spectra,such as infrared light. Said cameras may be configured to discernspectra that matches the emission properties of the light and totransmit images of the weight bar and the light, such as static photosor video, to an image processor, which may be configured to operateimage recognition software. The image processor may be installed withina camera rig made proximate to at least one of the cameras. As the userlifts the weight bar, images of the user lifting the weight bar may betaken by the cameras and image recognition software loaded onto theimage processor may be used to discern the location of said light in theimages. The image processor may be further configured to track themovements of said light in the images and to record the positions of thelight in the images as position data. The image processor may beconfigured to transmit the position data over a communication network tothe multimedia device having a data processor. The communicationsnetwork may comprise a wireless connection between the image processorand the multimedia device. The data processor may be further configuredto determine a map of the movement path of the weight bar using theposition data, to output the movement path as a performance metric, andto compare the movement path to an expected movement path associatedwith a particular lifting exercise. The multimedia device may beconfigured to display the movement path of the weight bar using a two-or three-dimensional graphical representation. The data processor may befurther configured to provide a quantitative or qualitative assessmentof the user's lift form based on the determined performance metrics.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 displays an isometric view of a collar configured to attach to aweight bar.

FIG. 2 displays an exploded view of the collar depicted in FIG. 1.

FIG. 3 displays a zoomed-out view of a collar attached to a weight bar.

FIG. 4 displays a zoomed-in view of a collar attached to a weight bar.

FIG. 5 displays a display screen of a multimedia device configured todisplay weightlifting performance metrics.

FIG. 6 displays the system architecture of a first embodiment of thepresent invention.

FIG. 7 displays a flowchart detailing the process by which the systemaccording to a first embodiment of the present invention obtainsphysical activity data and outputs performance metrics.

FIG. 8 displays the system architecture of an alternative embodiment ofthe present invention (a system additionally comprising a plurality ofcameras) configured to take images of the weight bar during useractivity.

FIG. 9 displays a flowchart detailing the process by which the system ofan alternative embodiment of the present invention (a systemadditionally comprising a plurality of cameras) obtains physicalactivity data and outputs performance metrics.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIG. 1 and FIG. 2 display different isometric views of a collar 101, thecollar being one element of a weight-lifting performance measurementsystem in accordance with the present invention. FIG. 1 portrays anon-exploded view of the collar while FIG. 2 portrays an exploded viewof the collar with subcomponents separated for illustrative purposes.The collar 101 may comprise a clamp 102 and a case mounted to the clamp,wherein the case may have a base 102 and a cover 103. The collar mayfurther comprise a circuit board 104 enclosed by said case, wherein thecircuit board may be mounted onto said base 102 and positioned beneathsaid cover 103. The base 102 and cover 103 may be integrally formed orthey may be separable and connectable components. The case may beconnected to the clamp via a fastener, such as a screw, or an adhesiveand may be formed of a moldable material, such as plastic. The clamp maycomprise an articulated hinge or it may be integrally formed from a ringof material. The clamp may further comprise a clasp for securing thecollar around a cylindrical weight bar.

Circuit board 103 may comprise at least one motion sensor, at least onetouch sensor, and a signal processor, wherein the signal processorcomprises electronic components that collect and process signals fromthe motion sensors and the touch sensors. Said motion sensors may beselected from at least one of a gyroscope, an accelerometer, and apressure sensor, such as a barometric altimeter. The motion sensors maybe sufficiently accurate to detect small changes in their measuredphysical parameter. For example, the barometric altimeter may beaccurate to at least 10 centimeters. Said touch sensors may comprisepads, screens, or buttons that sense changes in capacitance when inclose proximity to, or in contact with, a conductor. The motion sensorsand/or touch sensors may be mounted upon at least one programmable chiphaving an electrical connection to the circuit board. For example, thegyroscope and accelerometer may be mounted to the same programmablechip. The circuit board may further comprise a battery, a batterycharging circuit for charging said battery, and a power boost converterfor amplifying voltage to the battery charging circuit.

As depicted in FIG. 3 and FIG. 4, the collar 101 may be configured toattach to a weight bar 106. The collar may attach to the weight bar viaa clamp feature, a sliding friction grip, or another suitable means ofrigidly mounting to a cylindrical surface. The collar may be positionedat any point along the length of the weight bar. The collar may also beconfigured or sized to preferably be positioned on either of theweight-bearing end segments of the weight bar. As the weight bar islifted, dropped, or otherwise moved by an active user, the motionsensors electrically connected to the circuit board of the collar maytransmit signals to the signal processor, which may be configured toreceive as inputs the signals from the motion sensors and to convertsaid signals to physical activity data. Physical activity data maycomprise measurements by the sensors of physical parameters induced byactivity taken by the user. For example, as the user lifts the weightbar with the collar attached to either end, the signal processor may beconfigured to interpret signals from the accelerometer to measure theacceleration at which the weight bar is lifted, to interpret the signalsfrom the gyroscope to measure the orientation of the weight bar relativeto an axis, and to interpret the signals from the barometric altimeterto measure the height of the weight bar from the ground.

Said physical activity data may then be transmitted by the signalprocessor to a multimedia device. The multimedia device may comprise adata processor that determines performance metrics using the physicalactivity data received from the signal processor. As depicted in FIG. 5,sensors 110 relay signals to signal processor 120, which converts thesignals to physical activity data and then transmits said physicalactivity data to a data processor 150 within a multimedia device 140 viaa communication network 130. Physical activity data may be transmittedwirelessly, for example, via Bluetooth© or Bluetooth© low energytechnology. Performance metrics may comprise parameters thatcharacterize actions taken by the user during an activity involving theweight bar, and those performance metrics which are determined maycorrespond to particular activities. For example, performance metricsmay comprise lift velocity, which is the change in position of theweight bar during the time of the lift, lift force, which is the forcethe user exerts to raise the weight bar, and lift height, which is thevertical distance the weight bar is lifted from the ground as measuredat the apex of the lift. Other performance metrics may include theorientation of the weight bar, such as its tilt or deviation from ahorizontal axis, the movement path of the weight bar, i.e. the trackedthe number of repetitions of a lift, the duration of a lift, and theduration of a hold during a lift, among others. The data processor maybe capable of executing software instructions and may run a softwareapplication or App having an interface configured to accept inputs froma user. The software application may utilize algorithms to calculateperformance metrics by taking as inputs the physical activity datareceived from the signal processor. The software application or App maybe configured to display said performance metrics via a visual orgraphical representation on the multimedia device, such as via a displayscreen. Performance metrics may be calculated based on input from a useror may be automatically or programmatically determined. Alternatively,or in addition, the data processor may upload said performance metricsto another multimedia device or the internet. Said multimedia device maycomprise a personal computer, mobile tablet, smart phone, or activitytracker.

The performance metrics output by the data processor may also compriselift form. Lift form shall be understood to be a qualitative orquantitative assessment of a performed lift's proper technique, definedby predetermined values for performance metrics and movement paths ofthe weight bar as tracked by the data processor. Analysis of calculatedvalues for performance metrics by the data processor may result in theindication of proper or improper lift form depending on their comparisonto said predetermined values. The predetermined values may be defined bythe user and provided to the software application as inputs.Alternatively, the data processor may flag a lift as having proper orimproper form based on pre-programmed parameters that correspond toexpert opinions, athletic research, or weight training techniques knownto those skilled in the art.

An athlete, trainer, or other user may utilize the system in accordancewith the present invention to record performance metrics during weighttraining exercises and display them via a multimedia device. The systemmay operate in the following manner, the process of which is depicted inFIG. 6. First, the collar may be attached to the end of the weight bar.A touch sensor mounted to the collar and comprising a capacitive touchsensor may then be used to sense if the collar is on the weight bar(step 601). The user may then lift the weight bar while the signalprocessor in the circuit board receives signals from motion sensors,such as the accelerometer and gyroscope, as well as touch sensors (step602). Signals from the motion sensors may include acceleration force andtilt measurements from an accelerometer, angular velocity andorientation measurements from a gyroscope, and atmospheric pressuremeasurements from a barometric altimeter. The signal processor maydetermine physical activity data from said measurements. For example,the signal processor may determine the height of a lift from the changein atmospheric pressure measurements over time. If the signal processorreceives signals from the touch sensor that indicate the collar is onthe weight bar, it may transfer physical activity data gleaned from themotion sensors to a data processor in a multimedia device such as asmart phone or mobile tablet (step 603). The data transfer may be madewirelessly via Bluetooth©, low energy Bluetooth© or wireless internetprotocols. The device may be equipped with a data processor running aninstalled software application. The data processor may solve at leastone algorithm to determine if a lift has occurred by analyzing thephysical activity data (step 604). If the data processor determines thata lift of the weight bar has occurred, it may utilize filters todetermine performance metrics (step 605). The filters may comprise, forexample, a Kalman filter. If a lift has occurred, the performancemetrics may be saved by the software application or transmitted to anexternal storage device. The multimedia device may then display theperformance metrics to a user (step 606).

The amount and type of performance metrics that are derived anddisplayed may change depending on the type of lift being undertaken.Prior to lifting the weight bar with the collar mounted thereto, theathlete may select, via the software application, the type of lift theyare about to undertake. The software application may derive and displayperformance metrics that are specific to the type of lift performed. Forexample, the user may select from a list of lifting styles such as the“clean and jerk” or a “squat”.

In the case of a “clean and jerk” lift, the software application mayprocess data from the motion sensors to calculate the athlete's HipDrive Ratio, which is the measure of the force applied by the userduring the “clean” segment of the lift, as a weight bar is lifted fromthe floor to a position across the athlete's deltoids and clavicles. Thesoftware application may further calculate and report said athlete'sDrop Time, which is the time it takes to transition from the hip drivephase to the catch phase, as a weight bar is lifted from the groundwhile the athlete transitions to a vertical squatting position.

In the case of a “squat” lift, the software application may process datafrom the motion sensors to calculate the athlete's Squat Force, which isthe measure of the force that the athlete applies to the bar when whilein the bottom of the squat (the position at which the athlete's hips areclosest to the floor). The software application may further calculateand report said athlete's Up/Down Ratio, which is the ratio of the timeit takes the athlete to transition from the top of the squat (legsextended, hips above the knees), to the bottom (legs bent, hips towardthe ground) and the time it takes the athlete to transition from thebottom of the squat to the top.

In an alternative embodiment depicted in FIG. 7, the system formeasuring and reporting weight-training performance metrics may comprisea vision system for recording and capturing images and video of a userutilizing collar 101 during physical activity. Under this embodiment thesystem may further comprise a camera rig 160 proximate to or containingat least two cameras 170 mounted to the same or different retainingfixtures a known distance apart from each other. The cameras may bemounted a fixed distance apart from each other in order to bettertriangulate the position of the collar 101 in a composite image. Aplurality of more than two cameras may be mounted an equal distanceapart from each other. Each camera may comprise a cut-off filter forblocking light of a particular wavelength, such as infrared light. Thesystem of the second embodiment may further comprise a light fixture115, such as an LED, that may be mounted or affixed to the collar or ateither end of the weight bar. The light may be configured to emit at awavelength visible to the at least two cameras.

The cameras may be utilized to take images of a user lifting, rolling,tossing, or otherwise manipulating a weight bar with the collar 101attached. The cameras may be configured to transmit images or video ofthe bar, the collar, and the light source to an image processor 180. Theimage processor may be located on a local computer comprised withincamera rig 160 or in a server accessible over the internet. The imageprocessor may be configured to determine position data from the locationof recognizable features in the received images. The image processor 180may communicate over a network 130 with a multimedia device 140 having adata processor 150 and may be configured to transmit said position datato the data processor.

An athlete, trainer, or other use may utilize the system in accordancewith the second embodiment to record performance metrics during weighttraining exercises. Prior to utilizing the system, it may requirecalibration. The calibration process may ensure that the image processorincorporates accurate coordinates of the cameras and the weight bar inthree-dimensional space when determining position data. Calibration ofthe system in accordance with the second embodiment of the presentinvention may be performed via the following method:

Step 1: Attach a light source emitting light of a particular wavelengthand a collar in accordance with the present invention to an end of aweight bar. This step may be performed by the user. Alternatively, thelight may be pre-attached to the collar or to the weight bar prior toexercise activity.

Step 2: Position two cameras a known distance apart. This step may beperformed by the user. Alternatively, the cameras can be mounted to arigid or adjustable fixture that maintains an equal separation distancebetween the cameras at all times.

Step 3: Roll the weight bar across the floor in view of both cameras.This step may be performed by the user.

Step 4: Take images of the weight bar and the light source as it rollsacross the floor using both cameras.

Step 5: Utilize said image processor to establish the camera systemorientation based on detected light originating from the light source.

Step 6: Lift the weight bar to a known height. This step may beperformed by the user. The known height can encompass a predetermineddistance from the ground or may be relative to a user-definedcharacteristic, such as “shoulder height”.

Step 7: Take images of the weight bar and the light source at said knownheight using both cameras.

Step 8: Utilize said image processor to establish the distance of thelight, and therefore the weight bar, from the ground and from eachcamera.

An athlete, trainer, or other user may utilize the system in accordancewith the alternative embodiment of present invention to recordperformance metrics during weight training exercises and display themvia a multimedia device. The system may operate in the following manner,the process of which is depicted in FIG. 8. Once the system has beencalibrated, the user may raise and lower the weight bar in accordancewith a weight training exercise. As the weight bar is translated throughthe air by the user, each of the at least two cameras may take images ofthe light mounted to the weight bar (step 801). The cameras may transferthe images to an image processor (step 802), which may utilize imagerecognition software to recognize the location of the light within animage and determine position data of the light and weight bar inrelation to a known position (step 803). The image processor may savethe position data and then transfer the position data to a multimediadevice having a data processor (step 804). The device may be a smartphone, mobile tablet, or personal computer. The transfer may be madewirelessly via Bluetooth© technology, a wireless internet connection, orvia a wired connection on a local area network.

Next the data processor may determine the movement path of the weightbar by tracking the change in position data over time (step 805). Thedata processor may subsequently determine performance metrics related tothe activity performed by the user (step 806). For example the dataprocessor may be configured to calculate the acceleration of the barduring a lift by using the position data to determine its change invelocity over time. Other weightlifting performance metrics may becalculated by the data processor using algorithms that correspond to aparticular type of lift in the same manner as in the first embodiment. Adata processor may be configured to run a software application or App,wherein the software application is configured to calculate and displayweightlifting performance metrics using the position data output by theimage processor. Performance metrics and force graphs may be output tothe display screen of said multimedia device (step 807). Onceperformance metrics and force graphs have been displayed by the device,they may be uploaded by the device to an internet database via aBluetooth© technology or a wireless internet connection. Users may tracktheir progress by referring to the database via the user interface ofthe software application or via a web browser.

The derived performance metrics may be displayed to a user on thedisplay screen 907 of a multimedia device, as depicted in FIG. 9.Performance metrics may also be uploaded to the internet, where they maybe saved to a database and accessed via a web browser. Informationdisplayed by the device may include the type of lift being conducted,the total weight being lifted, graphs 108 displaying for example theforce exerted by the user during the time of the lift, the status of thesoftware application, and the derived performance metrics 109, amongother information. The software application may calculate and providecomparisons between the current lift and archival data of previouslifts. The data processor or the software application run by the dataprocessor may analyze performance metrics and output a grade, score,suggestion, evaluation, and/or other means of assessment to providefeedback to the user. Said grade, score, suggestion, evaluation and/orother means of assessment may be uploaded to a database and/or,displayed by the device.

It is contemplated that various combinations and/or sub-combinations ofthe specific features and aspects of the above embodiments may be madeand still fall within the scope of the invention. Accordingly, it shouldbe understood that various features and aspects of the disclosedembodiments may be combined with or substituted for one another in orderto form varying modes of the disclosed invention. Further it is intendedthat the scope of the present invention herein disclosed by way ofexamples should not be limited by the particular disclosed embodimentsdescribed above.

We claim:
 1. A system for measuring performance metrics, the systemcomprising: a collar configured to attach to a weight bar; at least onemotion sensor mounted to said collar; at least one touch sensor mountedto said collar; a signal processor configured to receive signals fromsaid motion-sensor and derive physical activity data using said signals;and a multimedia device, wherein the multimedia device comprises a dataprocessor configured to receive physical activity data from said signalprocessor and determine performance metrics using said physical activitydata.
 2. The system of claim 1, wherein said physical activity datacomprises at least one of: the acceleration of a weight bar; theorientation of a weight bar; and the distance of a weight bar from theground.
 3. The system of claim 1, wherein said performance metricscomprise at least one of: force exerted by a user lifting a weight bar;and lift form while lifting a weight bar.
 4. The system of claim 1,wherein said at least one motion-sensor comprises an accelerometer, andwherein the signal processor is configured to measure the accelerationof a weight bar using the signals from said accelerometer.
 5. The systemof claim 1, wherein said at least one motion-sensor comprises agyroscope, and wherein the signal processor is configured to measure theorientation of a weight bar using the signals from said gyroscope. 6.The system of claim 1, wherein said at least one motion sensor furthercomprises a pressure sensor.
 7. The system of claim 6, wherein thepressure sensor comprises a barometric altimeter, and wherein the signalprocessor is configured to measure the distance of a weight bar from theground using the signals from said barometric altimeter.
 8. The systemof claim 1, wherein said at least one touch sensor comprises acapacitive touch sensor.
 9. The system of claim 8, wherein said at leastone capacitive touch sensor is configured to sense contact between thecollar and a weight bar.
 10. The system of claim 1, wherein themultimedia device comprises a display.
 11. The system of claim 10,wherein the multimedia device is a Smartphone, a computer, or a mobiletablet.
 12. The system of claim 11, wherein the multimedia device isconfigured to store said performance metrics or transmit them to a user.13. A system for measuring performance metrics, the system comprising: acollar configured to attach to a weight bar; at least one motion sensormounted to said collar; a touch sensor mounted to said collar; at leastone light mounted to said collar; a camera rig comprising at least twocameras configured to view said collar; a signal processor configured toreceive signals from said at least one motion-sensor and derive physicalactivity data using said signals; an image processor configured toreceive images of said at least one light from said at least two camerasand derive position data using said images; a multimedia device, whereinthe multimedia device comprises a data processor configured to receivephysical activity data from said signal processor and position data fromsaid image processor and to determine performance metrics using saidphysical activity data and said position data.
 14. The system of claim13, wherein the light is an infrared light.
 15. The system of claim 14,wherein the at least two cameras are configured to view infrared light.16. The system of claim 13, wherein the at least two cameras are spacedan equal distance apart from each other.
 17. The system of claim 13,wherein said performance metrics comprise the movement path of a weightbar.